EFICAz2: Enzyme function inference by a combined approach enhanced by machine learning

BMC Bioinformatics

Volumn 10, Issue , 2009, Pages

  Arakaki, Adrian K ^a   Huang, Ying ^b   Skolnick, Jeffrey ^a  

^a GEORGIA INSTITUTE OF TECHNOLOGY   (United States)

^b UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CLASSIFICATION TREE MODEL; COMPARATIVE ANALYSIS; ENZYMATIC ACTIVITIES; MULTIPLE APPLICATIONS; MULTIPLE SEQUENCE ALIGNMENTS; OVERLAPPING COMPONENTS; PREDICTION PRECISION; SUPPORT VECTOR MACHINE MODELS;

BENCHMARKING; FORECASTING; SUPPORT VECTOR MACHINES; WEB SERVICES;

ENZYMES;

ENZYME; PROTEOME;

ACCURACY; AMINO ACID SEQUENCE; ARTICLE; ENZYME ACTIVITY; GENETIC ANALYSIS; HUMAN; INTERNET; MACHINE LEARNING; METABOLISM; PREDICTION; PROTEIN FAMILY; QUALITY CONTROL; SUPPORT VECTOR MACHINE; ARTIFICIAL INTELLIGENCE; BIOLOGY; CHEMISTRY; CLASSIFICATION; COMPUTER PROGRAM; FACTUAL DATABASE; METHODOLOGY; PHYSIOLOGY;

ARTIFICIAL INTELLIGENCE; COMPUTATIONAL BIOLOGY; DATABASES, FACTUAL; ENZYMES; HUMANS; SOFTWARE;

EID: 65349170082     PISSN: None     EISSN: 14712105     Source Type: Journal    
DOI: 10.1186/1471-2105-10-107     Document Type: Article

References (42)

1. Arakaki AK Tian W Skolnick J High precision multi-genome scale reannotation of enzyme function by EFICAz BMC Genomics 2006, 7:315. 1764738 17166279 10.1186/1471-2164-7-315
2. Freilich S Spriggs RV George RA Al-Lazikani B Swindells M Thornton JM The complement of enzymatic sets in different species J Mol Biol 2005, 349(4):745-763. 10.1016/j.jmb.2005.04.027 15896806
3. Webb EC Enzyme nomenclature 1992: Recommendations of the Nomenclature Committee of the International Union of Biochemistry and Molecular Biology on the nomenclature and classification of enzymes San Diego: Published for the International Union of Biochemistry and Molecular Biology by Academic Press 1992
4. Glasner ME Gerlt JA Babbitt PC Evolution of enzyme superfamilies Curr Opin Chem Biol 2006, 10(5):492-497. 10.1016/j.cbpa.2006.08.012 16935022
5. Ginsburg H Caveat emptor: Limitations of the automated reconstruction of metabolic pathways in Plasmodium Trends Parasitol 2008, 25(1):37-43. 10.1016/j.pt.2008.08.012 18986839
6. Becker SA Palsson BO Genome-scale reconstruction of the metabolic network in Staphylococcus aureus N315: An initial draft to the two-dimensional annotation BMC Microbiol 2005, 5:12. 1079850 15766389 10.1186/1471-2180-5-8
7. Guimera R Sales-Pardo M Amaral LAN A network-based method for target selection in metabolic networks Bioinformatics 2007, 23(13):1616-1622. 2149892 17463022 10.1093/bioinformatics/btm150
8. Pinney JW Papp B Hyland C Warnbua L Westhead DR McConkey GA Metabolic reconstruction and analysis for parasite genomes Trends Parasitol 2007, 23(11):548-554. 10.1016/j.pt.2007.08.013 17950669
9. Arakaki A Mezencev R Bowen N Huang Y McDonald J Skolnick J Identification of metabolites with anticancer properties by Computational Metabolomics Mol Cancer 2008, 7(1):57. 2453147 18559081 10.1186/1476-4598-7-57
10. Ma H Goryanin I Human metabolic network reconstruction and its impact on drug discovery and development Drug Discov Today 2008, 13(9-10):402-408. 10.1016/j.drudis.2008.02.002 18468557
11. Ouzounis CA Karp PD The past, present and future of genome-wide re-annotation Genome Biol 2002, 3: 2. COMMENT2001. 139008 11864365
12. Punta M Ofran Y The rough guide to in silico function prediction, or how to use sequence and structure information to predict protein function PLoS Comput Biol 2008, 4:10. e1000160 2518264 18974821 10.1371/ journal.pcbi.1000160
13. Gerlt JA Babbitt PC Can sequence determine function? Genome Biol 2000, 1:5. REVIEWS0005 138884 11178260 10.1186/gb-2000-1-5-reviews0005
14. Tian W Skolnick J How well is enzyme function conserved as a function of pairwise sequence identity? J Mol Biol 2003, 333(4):863-882. 10.1016/ j.jmb.2003.08.057 14568541
15. Kyrpides NC Ouzounis CA Whole-genome sequence annotation: 'Going wrong with confidence' Mol Microbiol 1999, 32(4):886-887. 10.1046/ j.1365-2958.1999.01380.x 10361291
16. Hegyi H Gerstein M Annotation transfer for genomics: Measuring functional divergence in multi-domain proteins Genome Res 2001, 11(10):1632-1640. 311165 11591640 10.1101/gr. 183801
17. Galperin MY Koonin EV Sources of systematic error in functional annotation of genomes: Domain rearrangement, non-orthologous gene displacement and operon disruption Silico Biol 1998, 1(1):55-67.
18. Devos D Valencia A Intrinsic errors in genome annotation Trends Genet 2001, 17(8):429-431. 10.1016/S0168-9525(01)02348-4 11485799
19. Brenner SE Errors in genome annotation Trends Genet 1999, 15(4):132-133. 10.1016/S0168-9525(99)01706-0 10203816
20. Gilks WR Audit B De Angelis D Tsoka S Ouzounis CA Modeling the percolation of annotation errors in a database of protein sequences Bioinformatics 2002, 18(12):1641-1649. 10.1093/bioinformatics/18.12.1641 12490449
21. Jones CE Brown AL Baumann U Estimating the annotation error rate of curated GO database sequence annotations BMC Bioinformatics 2007, 8:9. 1779800 17214880 10.1186/1471-2105-8-170
22. Arakaki AK Zhang Y Skolnick J Large-scale assessment of the utility of low-resolution protein structures for biochemical function assignment Bioinformatics 2004, 20(7):1087-1096. 10.1093/bioinformatics/bth044 14764543
23. Kristensen DM Ward RM Lisewski AM Erdin S Chen BY Fofanov VY Kimmel M Kavraki LE Lichtarge O Prediction of enzyme function based on 3D templates of evolutionarily important amino acids BMC Bioinformatics 2008, 9:17. 2219985 18190718 10.1186/1471-2105-9-17
24. Polacco BJ Babbitt PC Automated discovery of 3D motifs for protein function annotation Bioinformatics 2006, 22(6):723-730. 10.1093/ bioinformatics/btk038 16410325
25. Syed U Yona G Enzyme function prediction with interpretable models Computational Systems Biology Totowa, NJ: Humana Press McDermott J, Samudrala R, Bumgarner R, Montgomery K, Ireton R 2009, 541:187-199.
26. Kharchenko P Chen L Freund Y Vitkup D Church GM Identifying metabolic enzymes with multiple types of association evidence BMC Bioinformatics 2006, 7:177. 1450304 16571130 10.1186/1471-2105-7-177
27. Tian W Arakaki AK Skolnick J EFICAz: A comprehensive approach for accurate genome-scale enzyme function inference Nucleic Acids Res 2004, 32(21):6226-6239. 535665 15576349 10.1093/nar/gkh956
28. Cortes C Vapnik V SUPPORT-VECTOR NETWORKS Mach Learn 1995, 20(3):273-297.
29. Breiman L Classification and regression trees Belmont, Calif.: Wadsworth International Group 1984
30. KEGG: Kyoto Encyclopedia of Genes and Genomes ftp://ftp.genome.jp/pub/ kegg/
31. PROSITE Database ftp://us.expasy.org/databases/prosite/
32. Sigrist CJ Cerutti L Hulo N Gattiker A Falquet L Pagni M Bairoch A Bucher P PROSITE: A documented database using patterns and profiles as motif descriptors Brief Bioinform 2002, 3(3):265-274. 10.1093/bib/ 3.3.265 12230035
33. UniProt Knowledgebase Database ftp://us.expasy.org/databases/uniprot/
34. Kingsford C Salzberg SL What are decision trees? Nat Biotechnol 2008, 26(9):1011-1013. 10.1038/nbt0908-1011 18779814
35. 2 webservice http://cssb.biology.gatech.edu/skolnick/ webservice/EFICAz2/index.html
36. Espadaler J Eswar N Querol E Avilés FX Sali A Marti-Renom MA Oliva B Prediction of enzyme function by combining sequence similarity and protein interactions BMC Bioinformatics 2008, 9:249. 2430716 18505562 10.1186/1471-2105-9-249
37. Pfam Database ftp://ftp.sanger.ac.uk/pub/databases/Pfam/
38. Casari G Sander C Valencia A A method to predict functional residues in proteins Nat Struct Biol 1995, 2(2):171-178. 10.1038/nsb0295-171 7749921
39. Atchley WR Zhao J Fernandes AD Drüke T Solving the protein sequence metric problem Proc Natl Acad Sci USA 2005, 102(18):6395-6400. 1088356 15851683 10.1073/pnas.0408677102
40. Zhao Y Pinilla C Valmori D Martin R Simon R Application of support vector machines for T-cell epitopes prediction Bioinformatics 2003, 19(15):1978-1984. 10.1093/bioinformatics/btg255 14555632
41. LIBSVM: A library for support vector machines http://www.csie.ntu.edu.tw/ ~cjlin/libsvm
42. R Development Core Team R: A Language and Environment for Statistical Computing Vienna, Austria: R Foundation for Statistical Computing 2008